Systemic Risk Diagnostics : Coincident Indicators and Early Warning Signals

A macro-prudential policy maker can manage risks to financial stability only if current and future risks can be reliably assessed. We propose a novel framework to assess financial system risk. Using a dynamic factor framework based on state-space methods, we model latent macro-financial and credit risk components for a large data set comprising the U.S., the EU-27 area, and the rest of the world. Controlling for global, region-specific, and industry effects, we construct coincident measures ('thermometers') and forward looking indicators of financial distress and the likelihood of financial melt-down. We find that credit risk conditions can significantly and persistently de-couple from macro-financial fundamentals. Such decoupling can serve as an early warning signal for macro-prudential policy